Comparison of User Traffic Characteristics on Mobile-Access versus Fixed-Access Networks

  • Mikko V. J. Heikkinen
  • Arthur W. Berger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7192)

Abstract

We compare Web traffic characteristics of mobile- versus fixed-access end-hosts, where herein the term “mobile” refers to access via cell towers, using for example the 3G/UMTS standard, and the term “fixed” includes Wi-Fi access. It is well-known that connection speeds are in general slower over mobile-access networks, and also that often there is higher packet loss. We were curious whether this leads mobile-access users to have smaller connections. We examined the bytes-per-connection and packet loss based on packet retransmissions from a sampling of logs from servers of Akamai Technologies. We obtained 149 million connections, across 51 countries. The mean bytes-per-connection was typically larger for fixed-access: for two-thirds of the countries, it was at least one-third larger. Regarding distributions, we found that the difference between the bytes-per-connection for mobile- versus fixed-access was statistically significant for each of the countries, and likewise for packet loss. However, the difference is typically small. For some countries, mobile-access had the larger connections. As expected, mobile-access often had higher packet loss than fixed-access, but the reverse pertained for some countries. Typically packet loss increased during the busy period of the day, when mobile-access had a larger increase.

Keywords

Packet Loss Busy Period Packet Loss Rate Border Gateway Protocol Daily Demand 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Akamai: Akamai’s Edgescape Geo-Location Service. Tech. rep. (2010)Google Scholar
  2. 2.
    Akamai: State of the Internet 2Q/2010. Tech. rep. (2010)Google Scholar
  3. 3.
    Chen, K.T., Huang, P., Wang, G.S., Huang, C.Y., Lei, C.L.: On the Sensitivity of Online Game Playing Time to Network QoS. In: IEEE INFOCOM (2006)Google Scholar
  4. 4.
    Chen, K.T., Huang, C.Y., Huang, P., Lei, C.L.: Quantifying Skype User Satisfaction. SIGCOMM Comput. Commun. Rev. 36(4), 399–410 (2006)CrossRefGoogle Scholar
  5. 5.
    Cisco: Cisco Visual Networking Index: Forecast and Methodology, 2009-2014. Tech. rep. (2010)Google Scholar
  6. 6.
    Heikkinen, M.V.J., Berger, A.W.: Comparison of User Traffic Characteristics on Mobile-Access versus Fixed-Access Networks. Tech. Rep. MIT-CSAIL-TR-2011-028, MIT CSAIL (2011), http://hdl.handle.net/1721.1/62579
  7. 7.
    Hibberd, M.: Mobile Data Traffic Almost Triples Year on Year. Informa (2010)Google Scholar
  8. 8.
    Hossfeld, T., Tutschku, K., Andersen, F.U.: Mapping of File-Sharing onto Mobile Environments: Feasibility and Performance of eDonkey with GPRS. In: IEEE WCNC, pp. 2453–2458 (2005)Google Scholar
  9. 9.
    Kalden, R., Ekström, H.: Searching for Mobile Mice and Elephants in GPRS Networks. SIGMOBILE Mob. Comput. Commun. Rev. 8(4), 37–46 (2004)CrossRefGoogle Scholar
  10. 10.
    Sandvine: Fall 2010 Global Internet Phenomena. Tech. rep. (2010)Google Scholar
  11. 11.
    Svoboda, P.: Measurement and Modelling of Internet Traffic over 2.5 and 3G Cellular Core Networks. Ph.D. thesis, Vienna University of Technology (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mikko V. J. Heikkinen
    • 1
    • 2
    • 3
  • Arthur W. Berger
    • 3
    • 4
  1. 1.School of Electrical EngineeringAalto UniversityFinland
  2. 2.Helsinki Institute for Information Technology HIITFinland
  3. 3.Massachusetts Institute of TechnologyUSA
  4. 4.Akamai TechnologiesUSA

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